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feat: Add materialization, feature freshness, request latency, and push metrics to feature server - #6071
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| metrics: true | ||
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| The operator automatically exposes port 8000 and creates the corresponding |
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Should the operator also create the PodMonitor / ServiceMonitor resource owned by the FeatureStore resource for Prometheus operator to discover the metrics endpoint and configure the scraping?
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That would be a good enhancement, we can have CRD detection guard to avoid crashing on vanilla Kubernetes clusters without the Prometheus Operator. Will raise an issue for this.
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…sh metrics to feature server Signed-off-by: ntkathole <nikhilkathole2683@gmail.com>
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What this PR does / why we need it:
Adds rich Prometheus metrics to the Feast feature server covering areas that previously had no observability:
feature_countandfeature_view_countlabels so operators can correlate latency with request complexityPreviously the feature server only had inline CPU/memory monitoring. This PR introduces 10 new metric families covering the full request lifecycle, materialization pipeline, and data freshness.
New metrics
feast_feature_server_request_totalendpoint,statusfeast_feature_server_request_latency_secondsendpoint,feature_count,feature_view_countfeast_online_features_request_totalfeast_online_features_entity_countfeast_push_request_totalpush_source,modefeast_materialization_totalfeature_view,statusfeast_materialization_duration_secondsfeature_viewfeast_feature_freshness_secondsfeature_view,projectfeast_feature_server_cpu_usagefeast_feature_server_memory_usageConfiguration
Metrics are fully opt-in with zero overhead when disabled. Enable via CLI or YAML:
Per-category toggles let disable specific metric groups (e.g., keep CPU/memory but skip request latency). All categories default to true. The --metrics CLI flag works without any YAML config.